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Defending Pyramid's Design

From time to time, challenges to various aspects of :app:`Pyramid` design are lodged. To give context to discussions that follow, we detail some of the design decisions and trade-offs here. In some cases, we acknowledge that the framework can be made better and we describe future steps which will be taken to improve it; in some cases we just file the challenge as "noted", as obviously you can't please everyone all of the time.

Pyramid Has Zope Things In It, So It's Too Complex

On occasion, someone will feel compelled to post a mailing list message that reads something like this:

had a quick look at pyramid ... too complex to me and not really
understand for which benefits.. I feel should consider whether it's time
for me to step back to django .. I always hated zope (useless ?)
complexity and I love simple way of thinking

(Paraphrased from a real email, actually.)

Let's take this criticism point-by point.

Too Complex

  • If you can understand this hello world program, you can use Pyramid:

    from paste.httpserver import serve
    from pyramid.configuration import Configurator
    from pyramid.response import Response
    def hello_world(request):
        return Response('Hello world!')
    if __name__ == '__main__':
        config = Configurator()
        app = config.make_wsgi_app()
  • Pyramid is 5,000 lines of runtime code. Pylons 1.0 has about 3,000 lines of runtime code. Django has about 60,000 lines of runtime code. You'd practically need to bend the laws of space and time for Django to be simpler than Pyramid.

  • It has 600 or more pages of documentation (printed), covering topics from the very basic to the most advanced. Nothing is left undocumented, quite literally.

  • It has an awesome, very helpful community. Visit the #repoze and/or #pylons IRC channels on and see.

Hate Zope

I'm sorry you feel that way. The Zope brand has certainly taken its share of lumps over the years, and has a reputation for being insular and mysterious. But the word "Zope" is literally quite meaningless without qualification. What part of Zope do you hate? "Zope" is a brand, not a technology.

If it's Zope2-the-web-framework, Pyramid is not that. The primary designers and developers of Pyramid, if anyone, should know. We wrote Pyramid's predecessor (:mod:`repoze.bfg`), in part, because we knew that Zope 2 had usability issues and limitations. :mod:`repoze.bfg` (and now :app:`Pyramid`) was written to address these issues.

If it's Zope3-the-web-framework, Pyramid is definitely not that. Making use of lots of Zope 3 technologies is territory already staked out by the :term:`Grok` project. Save for the obvious fact that they're both web frameworks, :mod:`Pyramid` is very, very different than Grok. Grok exposes lots of Zope technologies to end users. On the other hand, if you need to understand a Zope-only concept while using Pyramid, then we've failed on some very basic axis.

If it's just the word Zope: it's, charitably, only guilt by association. You need to understand that just because a piece of software internally uses some package named, it doesn't turn the piece of software that uses it into "Zope". There is a lot of great software written that has the word Zope in its name. Zope is not some sort of monolithic thing, and a lot of its software is usable externally.

Zope Is Useless

It's not really the job of this document to defend Zope. But Zope has been around for over 10 years and has an incredibly large, active community. If you don't believe this, is an eye-opening reality check.

Love Simplicity

Years of effort have gone into honing this package and its documentation to make it as simple as humanly possible for developers to use. Everything is a tradeoff, of course, and people have their own ideas about what "simple" is. You may have a style difference if you believe Pyramid is complex. Its developers obviously disagree.

Pyramid Uses A Zope Component Architecture ("ZCA") Registry

:app:`Pyramid` uses a :term:`Zope Component Architecture` (ZCA) "component registry" as its :term:`application registry` under the hood. This is a point of some contention. :app:`Pyramid` is of a :term:`Zope` pedigree, so it was natural for its developers to use a ZCA registry at its inception. However, we understand that using a ZCA registry has issues and consequences, which we've attempted to address as best we can. Here's an introspection about :app:`Pyramid` use of a ZCA registry, and the trade-offs its usage involves.


The "global" API that may be used to access data in a ZCA "component registry" is not particularly pretty or intuitive, and sometimes it's just plain obtuse. Likewise, the conceptual load on a casual source code reader of code that uses the ZCA global API is somewhat high. Consider a ZCA neophyte reading the code that performs a typical "unnamed utility" lookup using the :func:`zope.component.getUtility` global API:

After this code runs, settings will be a Python dictionary. But it's unlikely that any "civilian" would know that just by reading the code. There are a number of comprehension issues with the bit of code above that are obvious.

First, what's a "utility"? Well, for the purposes of this discussion, and for the purpose of the code above, it's just not very important. If you really want to know, you can read this. However, still, readers of such code need to understand the concept in order to parse it. This is problem number one.

Second, what's this ISettings thing? It's an :term:`interface`. Is that important here? Not really, we're just using it as a "key" for some lookup based on its identity as a marker: it represents an object that has the dictionary API, but that's not very important in this context. That's problem number two.

Third of all, what does the getUtility function do? It's performing a lookup for the ISettings "utility" that should return.. well, a utility. Note how we've already built up a dependency on the understanding of an :term:`interface` and the concept of "utility" to answer this question: a bad sign so far. Note also that the answer is circular, a really bad sign.

Fourth, where does getUtility look to get the data? Well, the "component registry" of course. What's a component registry? Problem number four.

Fifth, assuming you buy that there's some magical registry hanging around, where is this registry? Homina homina... "around"? That's sort of the best answer in this context (a more specific answer would require knowledge of internals). Can there be more than one registry? Yes. So which registry does it find the registration in? Well, the "current" registry of course. In terms of :app:`Pyramid`, the current registry is a thread local variable. Using an API that consults a thread local makes understanding how it works non-local.

You've now bought in to the fact that there's a registry that is just "hanging around". But how does the registry get populated? Why, :term:`ZCML` of course. Sometimes. Or via imperative code. In this particular case, however, the registration of ISettings is made by the framework itself "under the hood": it's not present in any ZCML nor was it performed imperatively. This is extremely hard to comprehend. Problem number six.

Clearly there's some amount of cognitive load here that needs to be borne by a reader of code that extends the :app:`Pyramid` framework due to its use of the ZCA, even if he or she is already an expert Python programmer and whom is an expert in the domain of web applications. This is suboptimal.


First, the primary amelioration: :app:`Pyramid` does not expect application developers to understand ZCA concepts or any of its APIs. If an application developer needs to understand a ZCA concept or API during the creation of a :app:`Pyramid` application, we've failed on some axis.

Instead, the framework hides the presence of the ZCA registry behind special-purpose API functions that do use ZCA APIs. Take for example the function, which returns the userid present in the current request or None if no userid is present in the current request. The application developer calls it like so:

He now has the current user id.

Under its hood however, the implementation of authenticated_userid is this:

Using such wrappers, we strive to always hide the ZCA API from application developers. Application developers should just never know about the ZCA API: they should call a Python function with some object germane to the domain as an argument, and it should returns a result. A corollary that follows is that any reader of an application that has been written using :app:`Pyramid` needn't understand the ZCA API either.

Hiding the ZCA API from application developers and code readers is a form of enhancing "domain specificity". No application developer wants to need to understand the minutiae of the mechanics of how a web framework does its thing. People want to deal in concepts that are closer to the domain they're working in: for example, web developers want to know about users, not utilities. :app:`Pyramid` uses the ZCA as an implementation detail, not as a feature which is exposed to end users.

However, unlike application developers, framework developers, including people who want to override :app:`Pyramid` functionality via preordained framework plugpoints like traversal or view lookup must understand the ZCA registry API.

:app:`Pyramid` framework developers were so concerned about conceptual load issues of the ZCA registry API for framework developers that a replacement registry implementation named :mod:`repoze.component` was actually developed. Though this package has a registry implementation which is fully functional and well-tested, and its API is much nicer than the ZCA registry API, work on it was largely abandoned and it is not used in :app:`Pyramid`. We continued to use a ZCA registry within :app:`Pyramid` because it ultimately proved a better fit.


We continued using ZCA registry rather than disusing it in favor of using the registry implementation in :mod:`repoze.component` largely because the ZCA concept of interfaces provides for use of an interface hierarchy, which is useful in a lot of scenarios (such as context type inheritance). Coming up with a marker type that was something like an interface that allowed for this functionality seemed like it was just reinventing the wheel.

Making framework developers and extenders understand the ZCA registry API is a trade-off. We (the :app:`Pyramid` developers) like the features that the ZCA registry gives us, and we have long-ago borne the weight of understanding what it does and how it works. The authors of :app:`Pyramid` understand the ZCA deeply and can read code that uses it as easily as any other code.

But we recognize that developers who my want to extend the framework are not as comfortable with the ZCA registry API as the original developers are with it. So, for the purposes of being kind to third-party :app:`Pyramid` framework developers in, we've drawn some lines in the sand.

  1. In all "core" code, We've made use of ZCA global API functions such as zope.component.getUtility and zope.component.getAdapter the exception instead of the rule. So instead of:

    :app:`Pyramid` code will usually do:

    While the latter is more verbose, it also arguably makes it more obvious what's going on. All of the :app:`Pyramid` core code uses this pattern rather than the ZCA global API.

  2. We've turned the component registry used by :app:`Pyramid` into something that is accessible using the plain old dictionary API (like the :mod:`repoze.component` API). For example, the snippet of code in the problem section above was:

    In a better world, we might be able to spell this as:

    In this world, we've removed the need to understand utilities and interfaces, because we've disused them in favor of a plain dictionary lookup. We haven't removed the need to understand the concept of a registry, but for the purposes of this example, it's simply a dictionary. We haven't killed off the concept of a thread local either. Let's kill off thread locals, pretending to want to do this in some code that has access to the :term:`request`:

    In this world, we've reduced the conceptual problem to understanding attributes and the dictionary API. Every Python programmer knows these things, even framework programmers.

While :app:`Pyramid` still uses some suboptimal unnamed utility registrations, future versions of it will where possible disuse these things in favor of straight dictionary assignments and lookups, as demonstrated above, to be kinder to new framework developers. We'll continue to seek ways to reduce framework developer cognitive load.


Here are the main rationales involved in the :app:`Pyramid` decision to use the ZCA registry:

  • Pedigree. A nontrivial part of the answer to this question is "pedigree". Much of the design of :app:`Pyramid` is stolen directly from :term:`Zope`. Zope uses the ZCA registry to do a number of tricks. :app:`Pyramid` mimics these tricks, and, because the ZCA registry works well for that set of tricks, :app:`Pyramid` uses it for the same purposes. For example, the way that :app:`Pyramid` maps a :term:`request` to a :term:`view callable` is lifted almost entirely from Zope. The ZCA registry plays an important role in the particulars of how this request to view mapping is done.
  • Features. The ZCA component registry essentially provides what can be considered something like a "superdictionary", which allows for more complex lookups than retrieving a value based on a single key. Some of this lookup capability is very useful for end users, such as being able to register a view that is only found when the context is some class of object, or when the context implements some :term:`interface`.
  • Singularity. There's only one "place" where "application configuration" lives in a :app:`Pyramid` application: in a component registry. The component registry answers questions made to it by the framework at runtime based on the configuration of an application. Note: "an application" is not the same as "a process", multiple independently configured copies of the same :app:`Pyramid` application are capable of running in the same process space.
  • Composability. A ZCA component registry can be populated imperatively, or there's an existing mechanism to populate a registry via the use of a configuration file (ZCML). We didn't need to write a frontend from scratch to make use of configuration-file-driven registry population.
  • Pluggability. Use of the ZCA registry allows for framework extensibility via a well-defined and widely understood plugin architecture. As long as framework developers and extenders understand the ZCA registry, it's possible to extend :app:`Pyramid` almost arbitrarily. For example, it's relatively easy to build a ZCML directive that registers several views "all at once", allowing app developers to use that ZCML directive as a "macro" in code that they write. This is somewhat of a differentiating feature from other (non-Zope) frameworks.
  • Testability. Judicious use of the ZCA registry in framework code makes testing that code slightly easier. Instead of using monkeypatching or other facilities to register mock objects for testing, we inject dependencies via ZCA registrations and then use lookups in the code find our mock objects.
  • Speed. The ZCA registry is very fast for a specific set of complex lookup scenarios that :app:`Pyramid` uses, having been optimized through the years for just these purposes. The ZCA registry contains optional C code for this purpose which demonstrably has no (or very few) bugs.
  • Ecosystem. Many existing Zope packages can be used in :app:`Pyramid` with few (or no) changes due to our use of the ZCA registry and :term:`ZCML`.


If you only develop applications using :app:`Pyramid`, there's not much to complain about here. You just should never need to understand the ZCA registry or even know about its presence: use documented :app:`Pyramid` APIs instead. However, you may be an application developer who doesn't read API documentation because it's unmanly. Instead you read the raw source code, and because you haven't read the documentation, you don't know what functions, classes, and methods even form the :app:`Pyramid` API. As a result, you've now written code that uses internals and you've painted yourself into a conceptual corner as a result of needing to wrestle with some ZCA-using implementation detail. If this is you, it's extremely hard to have a lot of sympathy for you. You'll either need to get familiar with how we're using the ZCA registry or you'll need to use only the documented APIs; that's why we document them as APIs.

If you extend or develop :app:`Pyramid` (create new ZCML directives, use some of the more obscure "ZCML hooks" as described in :ref:`hooks_chapter`, or work on the :app:`Pyramid` core code), you will be faced with needing to understand at least some ZCA concepts. In some places it's used unabashedly, and will be forever. We know it's quirky, but it's also useful and fundamentally understandable if you take the time to do some reading about it.

Pyramid Uses Interfaces Too Liberally

In this TOPP Engineering blog entry, Ian Bicking asserts that the way :mod:`repoze.bfg` used a Zope interface to represent an HTTP request method added too much indirection for not enough gain. We agreed in general, and for this reason, :mod:`repoze.bfg` version 1.1 (and subsequent versions including :app:`Pyramid` 1.0+) added :term:`view predicate` and :term:`route predicate` modifiers to view configuration. Predicates are request-specific (or :term:`context` -specific) matching narrowers which don't use interfaces. Instead, each predicate uses a domain-specific string as a match value.

For example, to write a view configuration which matches only requests with the POST HTTP request method, you might write a @view_config decorator which mentioned the request_method predicate:

You might further narrow the matching scenario by adding an accept predicate that narrows matching to something that accepts a JSON response:

Such a view would only match when the request indicated that HTTP request method was POST and that the remote user agent passed application/json (or, for that matter, application/*) in its Accept request header.

"Under the hood", these features make no use of interfaces.

For more information about predicates, see :ref:`view_predicates_in_1dot1` and :ref:`route_predicates_in_1dot1`.

Many "prebaked" predicates exist. However, use of only "prebaked" predicates, however, doesn't entirely meet Ian's criterion. He would like to be able to match a request using a lambda or another function which interrogates the request imperatively. In :mod:`repoze.bfg` version 1.2, we acommodate this by allowing people to define "custom" view predicates:

The above view will only match when the first element of the request's :term:`subpath` is abc.

Pyramid "Encourages Use of ZCML"

:term:`ZCML` is a configuration language that can be used to configure the :term:`Zope Component Architecture` registry that :app:`Pyramid` uses as its application configuration. Often people claim that Pyramid "needs ZCML".

Quick answer: well, it doesn't. At least not anymore. In :mod:`repoze.bfg` (the predecessor to Pyramid) versions 1.0 and and 1.1, an application needed to possess a ZCML file for it to begin executing successfully. However, :mod:`repoze.bfg` 1.2 and greater (including :app:`Pyramid` 1.0) includes a completely imperative mode for all configuration. You will be able to make "single file" apps in this mode, which should help people who need to see everything done completely imperatively. For example, the very most basic :app:`Pyramid` "helloworld" program has become something like:

In this mode, no ZCML is required at all. Hopefully this mode will allow people who are used to doing everything imperatively feel more comfortable.

Pyramid Uses ZCML; ZCML is XML and I Don't Like XML

:term:`ZCML` is a configuration language in the XML syntax. Due to the "imperative configuration" feature (new in :mod:`repoze.bfg` 1.2), you don't need to use ZCML at all. But if you really do want to perform declarative configuration, perhaps because you want to build an extensible application, you will need to use and understand it.

:term:`ZCML` contains elements that are mostly singleton tags that are called declarations. For an example:

This declaration associates a :term:`view` with a route pattern.

All :app:`Pyramid` declarations are singleton tags, unlike many other XML configuration systems. No XML values in ZCML are meaningful; it's always just XML tags and attributes. So in the very common case it's not really very much different than an otherwise "flat" configuration format like .ini, except a developer can create a directive that requires nesting (none of these exist in :app:`Pyramid` itself), and multiple "sections" can exist with the same "name" (e.g. two <route> declarations) must be able to exist simultaneously.

You might think some other configuration file format would be better. But all configuration formats suck in one way or another. I personally don't think any of our lives would be markedly better if the declarative configuration format used by :app:`Pyramid` were YAML, JSON, or INI. It's all just plumbing that you mostly cut and paste once you've progressed 30 minutes into your first project. Folks who tend to agitate for another configuration file format are folks that haven't yet spent that 30 minutes.

Pyramid Uses "Model" To Represent A Node In The Graph of Objects Traversed

The :app:`Pyramid` documentation refers to the graph being traversed when :term:`traversal` is used as a "model graph". Some of the :app:`Pyramid` APIs also use the word "model" in them when referring to a node in this graph (e.g. pyramid.url.model_url).

A terminology overlap confuses people who write applications that always use ORM packages such as SQLAlchemy, which has a different notion of the definition of a "model". When using the API of common ORM packages, its conception of "model" is almost certainly not a directed acyclic graph (as may be the case in many graph databases). Often model objects must be explicitly manufactured by an ORM as a result of some query performed by a :term:`view`. As a result, it can be unnatural to think of the nodes traversed as "model" objects if you develop your application using traversal and a relational database. When you develop such applications, the things that :app:`Pyramid` refers to as "models" in such an application may just be stand-ins that perform a query and generate some wrapper for an ORM "model" (or set of ORM models). The graph might be composed completely of "model" objects (as defined by the ORM) but it also might not be.

The naming impedance mismatch between the way the term "model" is used to refer to a node in a graph in :app:`Pyramid` and the way the term "model" is used by packages like SQLAlchemy is unfortunate. For the purpose of avoiding confusion, if we had it to do all over again, we might refer to the graph that :app:`Pyramid` traverses a "node graph" or "object graph" rather than a "model graph", but since we've baked the name into the API, it's a little late. Sorry.

In our defense, many :app:`Pyramid` applications (especially ones which use :term:`ZODB`) do indeed traverse a graph full of model nodes. Each node in the graph is a separate persistent object that is stored within a database. This was the use case considered when coming up with the "model" terminology.

Pyramid Does Traversal, And I Don't Like Traversal

In :app:`Pyramid`, :term:`traversal` is the act of resolving a URL path to a :term:`model` object in an object graph. Some people are uncomfortable with this notion, and believe it is wrong.

This is understandable. The people who believe it is wrong almost invariably have all of their data in a relational database. Relational databases aren't naturally hierarchical, so "traversing" one like a graph is not possible. This problem is related to :ref:`model_traversal_confusion`.

Folks who deem traversal unilaterally "wrong" are neglecting to take into account that many persistence mechanisms are hierarchical. Examples include a filesystem, an LDAP database, a :term:`ZODB` (or another type of graph) database, an XML document, and the Python module namespace. It is often convenient to model the frontend to a hierarchical data store as a graph, using traversal to apply views to objects that either are the nodes in the graph being traversed (such as in the case of ZODB) or at least ones which stand in for them (such as in the case of wrappers for files from the filesystem).

Also, many website structures are naturally hierarchical, even if the data which drives them isn't. For example, newspaper websites are often extremely hierarchical: sections within sections within sections, ad infinitum. If you want your URLs to indicate this structure, and the structure is indefinite (the number of nested sections can be "N" instead of some fixed number), traversal is an excellent way to model this, even if the backend is a relational database. In this situation, the graph being traversed is actually less a "model graph" than a site structure.

But the point is ultimately moot. If you use :app:`Pyramid`, and you don't want to model your application in terms of traversal, you needn't use it at all. Instead, use :term:`URL dispatch` to map URL paths to views.

Pyramid Does URL Dispatch, And I Don't Like URL Dispatch

In :app:`Pyramid`, :term:`url dispatch` is the act of resolving a URL path to a :term:`view` callable by performing pattern matching against some set of ordered route definitions. The route definitions are examined in order: the first pattern which matches is used to associate the URL with a view callable.

Some people are uncomfortable with this notion, and believe it is wrong. These are usually people who are steeped deeply in :term:`Zope`. Zope does not provide any mechanism except :term:`traversal` to map code to URLs. This is mainly because Zope effectively requires use of :term:`ZODB`, which is a hierarchical object store. Zope also supports relational databases, but typically the code that calls into the database lives somewhere in the ZODB object graph (or at least is a :term:`view` related to a node in the object graph), and traversal is required to reach this code.

I'll argue that URL dispatch is ultimately useful, even if you want to use traversal as well. You can actually combine URL dispatch and traversal in :app:`Pyramid` (see :ref:`hybrid_chapter`). One example of such a usage: if you want to emulate something like Zope 2's "Zope Management Interface" UI on top of your object graph (or any administrative interface), you can register a route like <route name="manage" pattern="manage/*traverse"/> and then associate "management" views in your code by using the route_name argument to a view configuration, e.g. <view view=".some.callable" context=".some.Model" route_name="manage"/>. If you wire things up this way someone then walks up to for example, /manage/ob1/ob2, they might be presented with a management interface, but walking up to /ob1/ob2 would present them with the default object view. There are other tricks you can pull in these hybrid configurations if you're clever (and maybe masochistic) too.

Also, if you are a URL dispatch hater, if you should ever be asked to write an application that must use some legacy relational database structure, you might find that using URL dispatch comes in handy for one-off associations between views and URL paths. Sometimes it's just pointless to add a node to the object graph that effectively represents the entry point for some bit of code. You can just use a route and be done with it. If a route matches, a view associated with the route will be called; if no route matches, :app:`Pyramid` falls back to using traversal.

But the point is ultimately moot. If you use :app:`Pyramid`, and you really don't want to use URL dispatch, you needn't use it at all. Instead, use :term:`traversal` exclusively to map URL paths to views, just like you do in :term:`Zope`.

Pyramid Views Do Not Accept Arbitrary Keyword Arguments

Many web frameworks (Zope, TurboGears, Pylons 1.X, Django) allow for their variant of a :term:`view callable` to accept arbitrary keyword or positional arguments, which are "filled in" using values present in the request.POST or request.GET dictionaries or by values present in the "route match dictionary". For example, a Django view will accept positional arguments which match information in an associated "urlconf" such as r'^polls/(?P<poll_id>\d+)/$:

Zope, likewise allows you to add arbitrary keyword and positional arguments to any method of a model object found via traversal:

When this method is called as the result of being the published callable, the Zope request object's GET and POST namespaces are searched for keys which match the names of the positional and keyword arguments in the request, and the method is called (if possible) with its argument list filled with values mentioned therein. TurboGears and Pylons 1.X operate similarly.

:app:`Pyramid` has neither of these features. :mod:`pyramid` view callables always accept only context and request (or just request), and no other arguments. The rationale: this argument specification matching done aggressively can be costly, and :app:`Pyramid` has performance as one of its main goals, so we've decided to make people obtain information by interrogating the request object for it in the view body instead of providing magic to do unpacking into the view argument list. The feature itself also just seems a bit like a gimmick. Getting the arguments you want explicitly from the request via getitem is not really very hard; it's certainly never a bottleneck for the author when he writes web apps.

It is possible to replicate the Zope-like behavior in a view callable decorator, however, should you badly want something like it back. No such decorator currently exists. If you'd like to create one, Google for "zope mapply" and adapt the function you'll find to a decorator that pulls the argument mapping information out of the request.params dictionary.

A similar feature could be implemented to provide the Django-like behavior as a decorator by wrapping the view with a decorator that looks in request.matchdict.

It's possible at some point that :app:`Pyramid` will grow some form of argument matching feature (it would be simple to make it an always-on optional feature that has no cost unless you actually use it) for, but currently it has none.

Pyramid Provides Too Few "Rails"

By design, :app:`Pyramid` is not a particularly "opinionated" web framework. It has a relatively parsimonious feature set. It contains no built in ORM nor any particular database bindings. It contains no form generation framework. It has no administrative web user interface. It has no built in text indexing. It does not dictate how you arrange your code.

Such opinionated functionality exists in applications and frameworks built on top of :app:`Pyramid`. It's intended that higher-level systems emerge built using :app:`Pyramid` as a base. See also :ref:`apps_are_extensible`.

Pyramid Provides Too Many "Rails"

:app:`Pyramid` provides some features that other web frameworks do not. Most notably it has machinery which resolves a URL first to a :term:`context` before calling a view (which has the capability to accept the context in its argument list), and a declarative authorization system that makes use of this feature. Most other web frameworks besides :term:`Zope`, from which the pattern was stolen, have no equivalent core feature.

We consider this an important feature for a particular class of applications (CMS-style applications, which the authors are often commissioned to write) that usually use :term:`traversal` against a persistent object graph. The object graph contains security declarations as :term:`ACL` objects.

Having context-sensitive declarative security for individual objects in the object graph is simply required for this class of application. Other frameworks save for Zope just do not have this feature. This is one of the primary reasons that :app:`Pyramid` was actually written.

If you don't like this, it doesn't mean you can't use :app:`Pyramid`. Just ignore this feature and avoid configuring an authorization or authentication policy and using ACLs. You can build "Pylons-1.X-style" applications using :app:`Pyramid` that use their own security model via decorators or plain-old-imperative logic in view code.

Pyramid Is Too Big

"The :app:`Pyramid` compressed tarball is almost 2MB. It must be enormous!"

No. We just ship it with test code and helper templates. Here's a breakdown of what's included in subdirectories of the package tree:







pyramid/ (except for pyramd/tests and pyramid/paster_templates)


The actual :app:`Pyramid` runtime code is about 10% of the total size of the tarball omitting docs, helper templates used for package generation, and test code. Of the approximately 19K lines of Python code in the package, the code that actually has a chance of executing during normal operation, excluding tests and paster template Python files, accounts for approximately 5K lines of Python code. This is comparable to Pylons 1.X, which ships with a little over 2K lines of Python code, excluding tests.

Pyramid Has Too Many Dependencies

This is true. At the time of this writing, the total number of Python package distributions that :app:`Pyramid` depends upon transitively is 18 if you use Python 2.6 or 2.7, or 16 if you use Python 2.4 or 2.5. This is a lot more than zero package distribution dependencies: a metric which various Python microframeworks and Django boast.

The :mod:`zope.component` and :mod:`zope.configuration` packages on which :app:`Pyramid` depends have transitive dependencies on several other packages (:mod:`zope.schema`, :mod:`zope.i18n`, :mod:`zope.event`, :mod:`zope.interface`, :mod:`zope.deprecation`, :mod:`zope.i18nmessageid`). We've been working with the Zope community to try to collapse and untangle some of these dependencies. We'd prefer that these packages have fewer packages as transitive dependencies, and that much of the functionality of these packages was moved into a smaller number of packages.

:app:`Pyramid` also has its own direct dependencies, such as :term:`Paste`, :term:`Chameleon`, :term:`Mako` and :term:`WebOb`, and some of these in turn have their own transitive dependencies.

It should be noted that :app:`Pyramid` is positively lithe compared to :term:`Grok`, a different Zope-based framework. As of this writing, in its default configuration, Grok has 126 package distribution dependencies. The number of dependencies required by :app:`Pyramid` is many times fewer than Grok (or Zope itself, upon which Grok is based). :app:`Pyramid` has a number of package distribution dependencies comparable to similarly-targeted frameworks such as Pylons 1.X.

We try not to reinvent too many wheels (at least the ones that don't need reinventing), and this comes at the cost of some number of dependencies. However, "number of package distributions" is just not a terribly great metric to measure complexity. For example, the :mod:`zope.event` distribution on which :app:`Pyramid` depends has a grand total of four lines of runtime code. As noted above, we're continually trying to agitate for a collapsing of these sorts of packages into fewer distribution files.

Pyramid "Cheats" To Obtain Speed

Complaints have been lodged by other web framework authors at various times that :app:`Pyramid` "cheats" to gain performance. One claimed cheating mechanism is our use (transitively) of the C extensions provided by :mod:`zope.interface` to do fast lookups. Another claimed cheating mechanism is the religious avoidance of extraneous function calls.

If there's such a thing as cheating to get better performance, we want to cheat as much as possible. We optimize :app:`Pyramid` aggressively. This comes at a cost: the core code has sections that could be expressed more readably. As an amelioration, we've commented these sections liberally.

Pyramid Gets Its Terminology Wrong ("MVC")

"I'm a MVC web framework user, and I'm confused. :app:`Pyramid` calls the controller a view! And it doesn't have any controllers."

If you are in this camp, you might have come to expect things about how your existing "MVC" framework uses its terminology. For example, you probably expect that models are ORM models, controllers are classes that have methods that map to URLs, and views are templates. :app:`Pyramid` indeed has each of these concepts, and each probably works almost exactly like your existing "MVC" web framework. We just don't use the "MVC" terminology, as we can't square its usage in the web framework space with historical reality.

People very much want to give web applications the same properties as common desktop GUI platforms by using similar terminology, and to provide some frame of reference for how various components in the common web framework might hang together. But in the opinion of the author, "MVC" doesn't match the web very well in general. Quoting from the Model-View-Controller Wikipedia entry:

Though MVC comes in different flavors, control flow is generally as

  The user interacts with the user interface in some way (for
  example, presses a mouse button).

  The controller handles the input event from the user interface,
  often via a registered handler or callback and converts the event
  into appropriate user action, understandable for the model.

  The controller notifies the model of the user action, possibly
  resulting in a change in the model's state. (For example, the
  controller updates the user's shopping cart.)[5]

  A view queries the model in order to generate an appropriate
  user interface (for example, the view lists the shopping cart's
  contents). Note that the view gets its own data from the model.

  The controller may (in some implementations) issue a general
  instruction to the view to render itself. In others, the view is
  automatically notified by the model of changes in state
  (Observer) which require a screen update.

  The user interface waits for further user interactions, which
  restarts the cycle.

To the author, it seems as if someone edited this Wikipedia definition, tortuously couching concepts in the most generic terms possible in order to account for the use of the term "MVC" by current web frameworks. I doubt such a broad definition would ever be agreed to by the original authors of the MVC pattern. But even so, it seems most "MVC" web frameworks fail to meet even this falsely generic definition.

For example, do your templates (views) always query models directly as is claimed in "note that the view gets its own data from the model"? Probably not. My "controllers" tend to do this, massaging the data for easier use by the "view" (template). What do you do when your "controller" returns JSON? Do your controllers use a template to generate JSON? If not, what's the "view" then? Most MVC-style GUI web frameworks have some sort of event system hooked up that lets the view detect when the model changes. The web just has no such facility in its current form: it's effectively pull-only.

So, in the interest of not mistaking desire with reality, and instead of trying to jam the square peg that is the web into the round hole of "MVC", we just punt and say there are two things: the model, and the view. The model stores the data, the view presents it. The templates are really just an implementation detail of any given view: a view doesn't need a template to return a response. There's no "controller": it just doesn't exist. This seems to us like a more reasonable model, given the current constraints of the web.

Pyramid Applications are Extensible; I Don't Believe In Application Extensibility

Any :app:`Pyramid` application written obeying certain constraints is extensible. This feature is discussed in the :app:`Pyramid` documentation chapter named :ref:`extending_chapter`. It is made possible by the use of the :term:`Zope Component Architecture` and :term:`ZCML` within :app:`Pyramid`.

"Extensible", in this context, means:

  • The behavior of an application can be overridden or extended in a particular deployment of the application without requiring that the deployer modify the source of the original application.
  • The original developer is not required to anticipate any extensibility plugpoints at application creation time to allow fundamental application behavior to be overriden or extended.
  • The original developer may optionally choose to anticipate an application-specific set of plugpoints, which may be hooked by a deployer. If he chooses to use the facilities provided by the ZCA, the original developer does not need to think terribly hard about the mechanics of introducing such a plugpoint.

Many developers seem to believe that creating extensible applications is "not worth it". They instead suggest that modifying the source of a given application for each deployment to override behavior is more reasonable. Much discussion about version control branching and merging typically ensues.

It's clear that making every application extensible isn't required. The majority of web applications only have a single deployment, and thus needn't be extensible at all. However, some web applications have multiple deployments, and some have many deployments. For example, a generic "content management" system (CMS) may have basic functionality that needs to be extended for a particular deployment. That CMS system may be deployed for many organizations at many places. Some number of deployments of this CMS may be deployed centrally by a third party and managed as a group. It's useful to be able to extend such a system for each deployment via preordained plugpoints than it is to continually keep each software branch of the system in sync with some upstream source: the upstream developers may change code in such a way that your changes to the same codebase conflict with theirs in fiddly, trivial ways. Merging such changes repeatedly over the lifetime of a deployment can be difficult and time consuming, and it's often useful to be able to modify an application for a particular deployment in a less invasive way.

If you don't want to think about :app:`Pyramid` application extensibility at all, you needn't. You can ignore extensibility entirely. However, if you follow the set of rules defined in :ref:`extending_chapter`, you don't need to make your application extensible: any application you write in the framework just is automatically extensible at a basic level. The mechanisms that deployers use to extend it will be necessarily coarse: typically, views, routes, and resources will be capable of being overridden, usually via :term:`ZCML`. But for most minor (and even some major) customizations, these are often the only override plugpoints necessary: if the application doesn't do exactly what the deployment requires, it's often possible for a deployer to override a view, route, or resource and quickly make it do what he or she wants it to do in ways not necessarily anticipated by the original developer. Here are some example scenarios demonstrating the benefits of such a feature.

  • If a deployment needs a different styling, the deployer may override the main template and the CSS in a separate Python package which defines overrides.
  • If a deployment needs an application page to do something differently needs it to expose more or different information, the deployer may override the view that renders the page within a separate Python package.
  • If a deployment needs an additional feature, the deployer may add a view to the override package.

As long as the fundamental design of the upstream package doesn't change, these types of modifications often survive across many releases of the upstream package without needing to be revisited.

Extending an application externally is not a panacea, and carries a set of risks similar to branching and merging: sometimes major changes upstream will cause you to need to revisit and update some of your modifications. But you won't regularly need to deal wth meaningless textual merge conflicts that trivial changes to upstream packages often entail when it comes time to update the upstream package, because if you extend an application externally, there just is no textual merge done. Your modifications will also, for whatever its worth, be contained in one, canonical, well-defined place.

Branching an application and continually merging in order to get new features and bugfixes is clearly useful. You can do that with a :app:`Pyramid` application just as usefully as you can do it with any application. But deployment of an application written in :app:`Pyramid` makes it possible to avoid the need for this even if the application doesn't define any plugpoints ahead of time. It's possible that promoters of competing web frameworks dismiss this feature in favor of branching and merging because applications written in their framework of choice aren't extensible out of the box in a comparably fundamental way.

While :app:`Pyramid` application are fundamentally extensible even if you don't write them with specific extensibility in mind, if you're moderately adventurous, you can also take it a step further. If you learn more about the :term:`Zope Component Architecture`, you can optionally use it to expose other more domain-specific configuration plugpoints while developing an application. The plugpoints you expose needn't be as coarse as the ones provided automatically by :app:`Pyramid` itself. For example, you might compose your own :term:`ZCML` directive that configures a set of views for a prebaked purpose (e.g. restview or somesuch) , allowing other people to refer to that directive when they make declarations in the configure.zcml of their customization package. There is a cost for this: the developer of an application that defines custom plugpoints for its deployers will need to understand the ZCA or he will need to develop his own similar extensibility system.

Ultimately, any argument about whether the extensibility features lent to applications by :app:`Pyramid` are "good" or "bad" is somewhat pointless. You needn't take advantage of the extensibility features provided by a particular :app:`Pyramid` application in order to affect a modification for a particular set of its deployments. You can ignore the application's extensibility plugpoints entirely, and instead use version control branching and merging to manage application deployment modifications instead, as if you were deploying an application written using any other web framework.

Zope 3 Enforces "TTW" Authorization Checks By Default; Pyramid Does Not


:app:`Pyramid` performs automatic authorization checks only at :term:`view` execution time. Zope 3 wraps context objects with a security proxy <>, which causes Zope 3 to do also security checks during attribute access. I like this, because it means:

  1. When I use the security proxy machinery, I can have a view that conditionally displays certain HTML elements (like form fields) or prevents certain attributes from being modified depending on the the permissions that the accessing user possesses with respect to a context object.
  2. I want to also expose my model via a REST API using Twisted Web. If Pyramid performed authorization based on attribute access via Zope3's security proies, I could enforce my authorization policy in both :app:`Pyramid` and in the Twisted-based system the same way.


:app:`Pyramid` was developed by folks familiar with Zope 2, which has a "through the web" security model. This "TTW" security model was the precursor to Zope 3's security proxies. Over time, as the :app:`Pyramid` developers (working in Zope 2) created such sites, we found authorization checks during code interpretation extremely useful in a minority of projects. But much of the time, TTW authorization checks usually slowed down the development velocity of projects that had no delegation requirements. In particular, if we weren't allowing "untrusted" users to write arbitrary Python code to be executed by our application, the burden of "through the web" security checks proved too costly to justify. We (collectively) haven't written an application on top of which untrusted developers are allowed to write code in many years, so it seemed to make sense to drop this model by default in a new web framework.

And since we tend to use the same toolkit for all web applications, it's just never been a concern to be able to use the same set of restricted-execution code under two web different frameworks.

Justifications for disabling security proxies by default notwithstanding, given that Zope 3 security proxies are "viral" by nature, the only requirement to use one is to make sure you wrap a single object in a security proxy and make sure to access that object normally when you want proxy security checks to happen. It is possible to override the :app:`Pyramid` "traverser" for a given application (see :ref:`changing_the_traverser`). To get Zope3-like behavior, it is possible to plug in a different traverser which returns Zope3-security-proxy-wrapped objects for each traversed object (including the :term:`context` and the :term:`root`). This would have the effect of creating a more Zope3-like environment without much effort.

Microframeworks Have Smaller Hello World Programs

Self-described "microframeworks" exist: Bottle and Flask are two that are becoming popular. Bobo doesn't describe itself as a microframework, but its intended userbase is much the same. Many others exist. We've actually even (only as a teaching tool, not as any sort of official project) created one using BFG (the precursor to Pyramid). Microframeworks are small frameworks with one common feature: each allows its users to create a fully functional application that lives in a single Python file.

Some developers and microframework authors point out that Pyramid's "hello world" single-file program is longer (by about five lines) than the equivalent program in their favorite microframework. Guilty as charged; in a contest of "whose is shortest", Pyramid indeed loses.

This loss isn't for lack of trying. Pyramid aims to be useful in the same circumstance in which microframeworks claim dominance: single-file applications. But Pyramid doesn't sacrifice its ability to credibly support larger applications in order to achieve hello-world LoC parity with the current crop of microframeworks. Pyramid's design instead tries to avoid some common pitfalls associated with naive declarative configuration schemes. The subsections which follow explain the rationale.

Application Programmers Don't Control The Module-Scope Codepath (Import-Time Side-Effects Are Evil)

Please imagine a directory structure with a set of Python files in it:


The contents of

from config import decorator
from config import L
import pprint

def foo():

if __name__ == '__main__':
    import app2

The contents of

import app

def bar():

The contents of

L = []

def decorator(func):
    return func

If we cd to the directory that holds these files and we run python given the directory structure and code above, what happens? Presuably, our decorator decorator will be used twice, once by the decorated function foo in and once by the decorated function bar in Since each time the decorator is used, the list L in is appended to, we'd expect a list with two elements to be printed, right? Sadly, no:

[chrism@thinko]$ python
[<function foo at 0x7f4ea41ab1b8>,
 <function foo at 0x7f4ea41ab230>,
 <function bar at 0x7f4ea41ab2a8>]

By visual inspection, that outcome (three different functions in the list) seems impossible. We only defined two functions and we decorated each of those functions only once, so we believe that the decorator decorator will only run twice. However, what we believe is wrong because the code at module scope in our module was executed twice. The code is executed once when the script is run as __main__ (via python, and then it is executed again when imports the same file as app.

What does this have to do with our comparison to microframeworks? Many microframeworks in the current crop (e.g. Bottle, Flask) encourage you to attach configuration decorators to objects defined at module scope. These decorators execute arbitrarily complex registration code which populates a singleton registry that is a global defined in external Python module. This is analogous to the above example: the "global registry" in the above example is the list L.

Let's see what happens when we use the same pattern with the Groundhog microframework. Replace the contents of above with this:

from config import gh

def foo():
    return 'foo'

if __name__ == '__main__':
    import app2

Replace the contents of above with this:

import app'/bar/')
def bar():
    'return bar'

Replace the contents of above with this:

from groundhog import Groundhog
gh = Groundhog('myapp', 'seekrit')

How many routes will be registered within the routing table of the "gh" Groundhog application? If you answered three, you are correct. How many would a casual reader (and any sane developer) expect to be registered? If you answered two, you are correct. Will the double registration be a problem? With our fictional Groundhog framework's route method backing this application, not really. It will slow the application down a little bit, because it will need to miss twice for a route when it does not match. Will it be a problem with another framework, another application, or another decorator? Who knows. You need to understand the application in its totality, the framework in its totality, and the chronology of execution to be able to predict what the impact of unintentional code double-execution will be.

The encouragement to use decorators which perform population of an external registry has an unintended consequence: the application developer now must assert ownership of every codepath that executes Python module scope code. This code is presumed by the current crop of decorator-based microframeworks to execute once and only once; if it executes more than once, weird things will start to happen. It is up to the application developer to maintain this invariant. Unfortunately, however, in reality, this is an impossible task, because, Python programmers do not own the module scope codepath, and never will. Microframework programmers therefore will at some point then need to start reading the tea leaves about what might happen if module scope code gets executed more than once like we do in the previous paragraph. This is a really pretty poor situation to find yourself in as an application developer: you probably didn't even know you signed up for the job, because the documentation offered by decorator-based microframeworks don't warn you about it.

Python application programmers do not control the module scope codepath. Anyone who tries to sell you on the idea that they do is simply mistaken. Test runners that you may want to use to run your code's tests often perform imports of arbitrary code in strange orders that manifest bugs like the one demonstrated above. API documentation generation tools do the same. Some (mutant) people even think it's safe to use the Python reload command or delete objects from sys.modules, each of which has hilarious effects when used against code that has import-time side effects. When Python programmers assume they can use the module-scope codepath to run arbitrary code (especially code which populates an external registry), and this assumption is challenged by reality, the application developer is often required to undergo a painful, meticulous debugging process to find the root cause of an inevitably obscure symptom. The solution is often to rearrange application import ordering or move an import statement from module-scope into a function body. The rationale for doing so can never be expressed adequnately in the checkin message which accompanies the fix or documented succinctly enough for the benefit of the rest of the development team so that the problem never happens again. It will happen again next month too, especially if you are working on a project with other people who haven't yet internalized the lessons you learned while you stepped through module-scope code using pdb.

Folks who have a large investment in eager decorator-based configuration that populates an external data structure (such as microframework authors) may argue that the set of circumstances I outlined above is anomalous and contrived. They will argue that it just will never happen. If you never intend your application to grow beyond one or two or three modules, that's probably true. However, as your codebase grows, and becomes spread across a greater number of modules, the circumstances in which module-scope code will be executed multiple times will become more and more likely to occur and less and less predictable. It's not responsible to claim that double-execution of module-scope code will never happen. It will; it's just a matter of luck, time, and application complexity.

If microframework authors do admit that the circumstance isn't contrived, they might then argue that "real" damage will never happen as the result of the double-execution (or triple-execution, etc) of module scope code. You would be wise to disbelieve this assertion. The potential outcomes of multiple execution are too numerous to predict because they involve delicate relationships between application and framework code as well as chronology of code execution. It's literally impossible for a framework author to know what will happen in all circumstances ("X is executed, then Y, then X again.. a train leaves Chicago at 50 mph... "). And even if given the gift of omniscience for some limited set of circumstances, the framework author almost certainly does not have the double-execution anomaly in mind when coding new features. He's thinking of adding a feature, not protecting against problems that might be caused by the 1% multiple execution case. However, any 1% case may cause 50% of your pain on a project, so it'd be nice if it never occured.

Responsible microframeworks actually offer a back-door way around the problem. They allow you to disuse decorator based configuration entirely. Instead of requiring you to do the following:

gh = Groundhog('myapp', 'seekrit')

def foo():
    return 'foo'

if __name__ == '__main__':

They allow you to disuse the decorator syntax and go almost-all-imperative:

def foo():
    return 'foo'

gh = Groundhog('myapp', 'seekrit')

if __name__ == '__main__':
    gh.add_route(foo, '/foo/')

This is a generic mode of operation that is encouraged in the Pyramid documentation. Some existing microframeworks (Flask, in particular) allow for it as well. None (other than Pyramid) encourage it. If you never expect your application to grow beyond two or three or four or ten modules, it probably doesn't matter very much which mode you use. If your application grows large, however, imperative configuration can provide better predictability.


Astute readers may notice that Pyramid has configuration decorators too. Aha! Don't these decorators have the same problems? No. These decorators do not populate an external Python module when they are executed. They only mutate the functions (and classes and methods) they're attached to. These mutations must later be found during a "scan" process that has a predictable and structured import phase. Module-localized mutation is actually the best-case circumstance for double-imports; if a module only mutates itself and its contents at import time, if it is imported twice, that's OK, because each decorator invocation will always be mutating an independent copy of the object its attached to, not a shared resource like a registry in another module. This has the effect that double-registrations will never be performed.

Routes (Usually) Need Relative Ordering

Consider the following simple Groundhog application:

from groundhog import Groundhog
app = Groundhog('myapp', 'seekrit')

def admin():
    return '<html>admin page</html>'

def action():
    if action == 'add':
       return '<html>add</html>'
    if action == 'delete':
       return '<html>delete</html>'
    return app.abort(404)

if __name__ == '__main__':

If you run this application and visit the URL /admin, you will see "admin" page. This is the intended result. However, what if you rearrange the order of the function definitions in the file?

from groundhog import Groundhog
app = Groundhog('myapp', 'seekrit')

def action():
    if action == 'add':
       return '<html>add</html>'
    if action == 'delete':
       return '<html>delete</html>'
    return app.abort(404)

def admin():
    return '<html>admin page</html>'

if __name__ == '__main__':

If you run this application and visit the URL /admin, you will now be returned a 404 error. This is probably not what you intended. The reason you see a 404 error when you rearrange function definition ordering is that routing declarations expressed via our microframework's routing decorators have an ordering, and that ordering matters.

In the first case, where we achieved the expected result, we first added a route with the pattern /admin, then we added a route with the pattern /:action by virtue of adding routing patterns via decorators at module scope. When a request with a PATH_INFO of /admin enters our application, the web framework loops over each of our application's route patterns in the order in which they were defined in our module. As a result, the view associated with the /admin routing pattern will be invoked: it matches first. All is right with the world.

In the second case, where we did not achieve the expected result, we first added a route with the pattern /:action, then we added a route with the pattern /admin. When a request with a PATH_INFO of /admin enters our application, the web framework loops over each of our application's route patterns in the order in which they were defined in our module. As a result, the view associated with the /:action routing pattern will be invoked: it matches first. A 404 error is raised. This is not what we wanted; it just happened due to the order in which we defined our view functions.

You may be willing to maintain an ordering of your view functions which reifies your routing policy. Your application may be small enough where this will never cause an issue. If it becomes large enough to matter, however, I don't envy you. Maintaining that ordering as your application grows larger will be difficult. At some point, you will also need to start controlling import ordering as well as function definition ordering. When your application grows beyond the size of a single file, and when decorators are used to register views, the non-__main__ modules which contain configuration decorators must be imported somehow for their configuration to be executed.

Does that make you a little uncomfortable? It should, because :ref:`you_dont_own_modulescope`.

"Stacked Object Proxies" Are Too Clever / Thread Locals Are A Nuisance

In another manifestation of "import fascination", some microframeworks use the import statement to get a handle to an object which is not logically global:

from flask import request

@app.route('/login', methods=['POST', 'GET'])
def login():
    error = None
    if request.method == 'POST':
        if valid_login(request.form['username'],
            return log_the_user_in(request.form['username'])
            error = 'Invalid username/password'
    # this is executed if the request method was GET or the
    # credentials were invalid

The Pylons 1.X web framework uses a similar strategy. It calls these things "Stacked Object Proxies", so, for purposes of this discussion, I'll do so as well.

Import statements in Python (import foo, from bar import baz) are most frequently performed to obtain a reference to an object defined globally within an external Python module. However, in "normal" programs, they are never used to obtain a reference to an object that has a lifetime measured by the scope of the body of a function. It would be absurd to try to import, for example, a variable named i representing a loop counter defined in the body of a function. For example, we'd never try to import i from the code below:

def afunc():
    for i in range(10):
        print i

By its nature, the request object created as the result of a WSGI server's call into a long-lived web framework cannot be global, because the lifetime of a single request will be much shorter than the lifetime of the process running the framework. A request object created by a web framework actually has more similarity to the i loop counter in our example above than it has to any comparable importable object defined in the Python standard library or in "normal" library code.

However, systems which use stacked object proxies promote locally scoped objects such as request out to module scope, for the purpose of being able to offer users a "nice" spelling involving import. They, for what I consider dubious reasons, would rather present to their users the canonical way of getting at a request as from framework import request instead of a saner from myframework.threadlocals import get_request; request = get_request() even though the latter is more explicit.

It would be most explicit if the microframeworks did not use thread local variables at all. Pyramid view functions are passed a request object; many of Pyramid's APIs require that an explicit request object be passed to them. It is possible to retrieve the current Pyramid request as a threadlocal variable but it is a "in case of emergency, break glass" type of activity. This explicitness makes Pyramid view functions more easily unit testable, as you don't need to rely on the framework to manufacture suitable "dummy" request (and other similarly-scoped) objects during test setup. It also makes them more likely to work on arbitrary systems, such as async servers that do no monkeypatching.

Explicitly WSGI

Some microframeworks offer a run() method of an application object that executes a default server configuration for easy execution.

Pyramid doesn't currently try to hide the fact that its router is a WSGI application behind a convenience run() API. It just tells people to import a WSGI server and use it to serve up their Pyramid application as per the documentation of that WSGI server.

The extra lines saved by abstracting away the serving step behind run() seem to have driven dubious second-order decisions related to API in some microframeworks. For example, Bottle contains a ServerAdapter subclass for each type of WSGI server it supports via its mechanism. This means that there exists code in that depends on the following modules: wsgiref, flup, paste, cherrypy, fapws, tornado, google.appengine, twisted.web, diesel, gevent, gunicorn, eventlet, and rocket. You choose the kind of server you want to run by passing its name into the run method. In theory, this sounds great: I can try Bottle out on gunicorn just by passing in a name! However, to fully test Bottle, all of these third-party systems must be installed and functional; the Bottle developers must monitor changes to each of these packages and make sure their code still interfaces properly with them. This expands the packages required for testing greatly; this is a lot of requirements. It is likely difficult to fully automate these tests due to requirements conflicts and build issues.

As a result, for single-file apps, we currently don't bother to offer a run() shortcut; we tell folks to import their WSGI server of choice and run it "by hand". For the people who want a server abstraction layer, we suggest that they use PasteDeploy. In PasteDeploy-based systems, the onus for making sure that the server can interface with a WSGI application is placed on the server developer, not the web framework developer, making it more likely to be timely and correct.

Wrapping Up

Here's a diagrammed version of the simplest pyramid application, where comments take into account what we've discussed in the :ref:`microframeworks_smaller_hello_world` section.

from webob import Response                 # explicit response objects, no TL
from paste.httpserver import serve         # explicitly WSGI

def hello_world(request):  # accepts a request; no request thread local reqd
    # explicit response object means no response threadlocal
    return Response('Hello world!')

if __name__ == '__main__':
    from pyramid.configuration import Configurator
    config = Configurator()       # no global application object.
    config.add_view(hello_world)  # explicit non-decorator registration
    app = config.make_wsgi_app()  # explicitly WSGI
    serve(app, host='')    # explicitly WSGI

Other Challenges

Other challenges are encouraged to be sent to the Pylons-devel maillist. We'll try to address them by considering a design change, or at very least via exposition here.

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